Wheat seeding rate for spread and distinct row seed placement with air seeders
Bibliographic record
Abstract
Air (pneumatic) seeding systems that have seed row opener options that spread seed rather than place it in distinct rows may allow producers to uniformly distribute plants and increase seeding rates to improve cereal crop yield. A study was conducted to determine if seed placement configuration influenced hard red spring wheat (Triticum aestivum L.) response to seeding rate. The study was carried out at Melfort, SK, from 1997 to 1999, using three seed configurations (23 cm and 30 cm distinct row with a hoe opener; and a 20 cm spread using a 28 cm sweep on 23 cm row spacing) and four seeding rates (67, 100, 134, and 167 kg ha –1 ). Grain yield increased 6% when seeding rate was increased from 100 (recommended rate) to 168 kg ha –1 in 1997. Improved grain yield with increased seeding rates was related to greater kernels head –1 . In the 2 following years, yield decreased by 9% when seeding rate was increased from 100 to 168 kg ha –1 . Yield reductions in these years were associated with high yield potential (high soil N availability) and lodging, that in turn resulted in decreased kernels head –1 and kernel weight with increased seeding rates. Grain yield did not differ between the sweep and distinct rows, regardless of the seeding rate. Furthermore, the similar yields among the three seed configurations occurred despite lodging being less with sweeps compared with 23 or 30 cm row spacing at the highest seeding rate in 1998. The increased distance between wheat plants with sweeps did not improve grain yields as a result of reduced inter-plant competition, regardless of seeding rate. This absence of grain yield differences between the sweep and distinct row placement illustrates the yield stability associated with Canadian hard red spring wheat cultivars through yield component compensation. Key words: Wheat (Triticum aestivum L.), row spacing, seeding rate, lodging, seed placement
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".